Automatic building assessment

• US 9,082,015 B2
• Filed: 03/15/2013
• Issued: 07/14/2015
• Est. Priority Date: 03/15/2013
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Christopulos, Nicholas U., Maurer, Jonathan D., Tofte, Nathan L., Schmidgall, Roger D., Freeman, James M.
• Primary Examiner(s): Koziol, Stephen R
• Assistant Examiner(s): CHOI, TIMOTHY WING HO
• Application Number:
  US13/839,634
• Publication Number:
  US 20140270492A1
• Time in Patent Office: 851 Days
• Field of Search: 382159-161, 382181-231
• US Class Current: 1/1
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06F 18/241 relating to the classification model, e.g. parametric or non-parametric approaches
• CPC Class Codes: G06F 18/2413 based on distances to training or reference patterns
• CPC Class Codes: G06F 18/243 relating to the number of classes
• CPC Class Codes: G06F 18/2431 Multiple classes
• CPC Class Codes: G06F 2218/12 Classification; Matching
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06Q 50/16 Real estate
• CPC Class Codes: G06V 20/176 Urban or other man-made structures
• CPC Class Codes: G06V 20/39 Urban scenes
• CPC Class Codes: G06V 2201/10 Recognition assisted with metadata

Abstract

Disclosed systems and methods automatically assess buildings and structures. A device may receive one or more images of a structure, such as a building or portion of the building, and then label and extract relevant data. The device may then train a system to automatically assess other data describing similar buildings or structures based on the labeled and extracted data. After training, the device may then automatically assess new data, and the assessment results may be sent directly to a client or to an agent for review and/or processing.

Claims

1. A computer-implemented method in a computing device having a processor for automatically assessing a building structure, the method comprising:

automatically receiving, using the processor, a first set of captured data points describing a first plurality of building structures;

automatically extracting, using the processor, feature data describing physical characteristics of the first plurality of building structures;

automatically training, using the processor, a building structure classification system based on the extracted feature data;

automatically verifying, using the processor, the training of the building structure classification system using data points describing one or more additional building structures having known characteristics;

automatically receiving, using the processor, a second set of captured data points describing a particular building structure, wherein the second set of captured data points includes a plurality of separately captured sets of data points;

automatically classifying, using the processor, at least a portion of the second set of captured data points based on the building structure classification system and further based on one or more classification rules limiting categories of the feature data used in classifying the second set of captured data points, wherein classifying the at least a portion of the second set of captured data points includes determining a classification indicating the structural condition of a feature of the particular building structure; and

automatically outputting, using the processor, one or more results of classifying the at least a portion of the second set of captured data points.

2. The method of claim 1 further comprising:

displaying the one or more results of classifying the at least a portion of the second set of captured data points overlaid on one or more images of the building structure.

3. The method of claim 2, wherein displaying the one or more results of classifying the at least a portion of the second set of captured data points is performed in real time as a user scans portions of the image.

4. The method of claim 1 wherein the second set of captured data points corresponds to a portion of one or more images of the building structure being reviewed by a user.

5. The method of claim 1, wherein the classification evaluates at least one of the age, type, construction, condition, or pre-existing damage of the building structure.

6. The method of claim 1, wherein the building structure is assessed as part of at least one of:

an insurance claim assessment, an insurance underwriting process, structural analysis, building code enforcement, estimation, appraisal and assessment, or remodeling.

7. A non-transitory computer-readable storage medium including non-transitory computer readable instruction to be executed on one or more processors of a system for automatically assessing a building structure, the instructions when executed causing the one or more processors to:

receive a first set of captured data points describing a first plurality of building structures;

extract feature data describing physical characteristics of the first plurality of building structures;

train a building structure classification system based on the extracted feature data;

verify the training of the building structure classification system using data points describing one or more additional building structures having known characteristics;

receive a second set of captured data points describing a particular building structure, wherein the second set of captured data points includes a plurality of separately captured sets of data points;

classify at least a portion of the second set of captured data points based on the building structure classification system and further based on one or more classification rules limiting categories of the feature data used in classifying the second set of captured data points, wherein classifying the at least a portion of the second set of captured data points includes determining a classification indicating the structural condition of a feature of the particular building structure; and

output one or more results of classifying the at least a portion of the second set of captured data points.

8. The non-transitory computer-readable storage medium of claim 7, wherein the instructions when executed further cause the one or more processors to:

display the one or more results of classifying the at least a portion of the second set of captured data points overlaid on one or more images of the building structure.

9. The non-transitory computer-readable storage medium of claim 8 wherein displaying the one or more results of classifying the at least a portion of the second set of captured data points is performed in real time as a user scans portions of the image.

10. The non-transitory computer-readable storage medium of claim 7 wherein the second set of captured data points corresponds to a portion of the one or more images of the building structure being reviewed by a user.

11. The non-transitory computer-readable storage medium of claim 7, wherein classifying at least a portion of the second set of captured data points based on the building structure classification system comprises evaluating at least one of the age, type, construction, condition, or pre-existing damage of the building structure.

12. The non-transitory computer-readable storage medium of claim 7, wherein the building structure is assessed as part of an insurance claim assessment.

13. A device operative to assess a building structure, the device comprising:

one or more processors;

a memory unit coupled to the one or more processors and storing executable instructions that when executed by the one or more processors cause the device to;

receive a first set of captured data points describing a first plurality of building structures;

extract feature data describing physical characteristics of the first plurality of building structures;

train a building structure classification system based on the extracted feature data;

verify the training of the building structure classification system using data points describing one or more additional building structures having known characteristics;

receive a second set of captured data points describing a particular building structure, wherein the second set of captured data points includes a plurality of separately captured sets of data points;

classify at least a portion of the second set of captured data points based on the building structure classification system and further based on one or more classification rules limiting categories of the feature data used in classifying the second set of captured data points, wherein classifying the at least a portion of the second set of captured data points includes determining a classification indicating the structural condition of a feature of the particular building structure; and

output one or more results of classifying the at least a portion of the second set of captured data points.

14. The device of claim 13, wherein the executable instructions stored in the memory unit, when executed by the one or more processors, further cause the device to:

display the one or more results of classifying the at least a portion of the second set of captured data points overlaid on one or more images of the building structure.

15. The device of claim 13 wherein displaying the one or more results of classifying the at least a portion of the second set of captured data points is performed in real time as a user scans portions of the image.

16. The device of claim 13 wherein the second set of captured data points corresponds to a portion of the one or more images of the building structure being reviewed by a user.

17. The device of claim 13, wherein classifying at least a portion of the second set of captured data points based on the building structure classification system comprises evaluating at least one of the age, type, construction, condition, or pre-existing damage of the building structure.

18. The device of claim 13, wherein the building structure is assessed as part of an insurance claim assessment.